Skip to main content
×
Home
    • Aa
    • Aa

Justifying answer sets using argumentation

  • CLAUDIA SCHULZ (a1) and FRANCESCA TONI (a1)
Abstract
Abstract

An answer set is a plain set of literals which has no further structure that would explain why certain literals are part of it and why others are not. We show how argumentation theory can help to explain why a literal is or is not contained in a given answer set by defining two justification methods, both of which make use of the correspondence between answer sets of a logic program and stable extensions of the assumption-based argumentation (ABA) framework constructed from the same logic program. Attack Trees justify a literal in argumentation-theoretic terms, i.e. using arguments and attacks between them, whereas ABA-Based Answer Set Justifications express the same justification structure in logic programming terms, that is using literals and their relationships. Interestingly, an ABA-Based Answer Set Justification corresponds to an admissible fragment of the answer set in question, and an Attack Tree corresponds to an admissible fragment of the stable extension corresponding to this answer set.

Copyright
Linked references
Hide All

This list contains references from the content that can be linked to their source. For a full set of references and notes please see the PDF or HTML where available.

T. Arora , R. Ramakrishnan , W. G. Roth , P. Seshadri and D. Srivastava 1993. Explaining program execution in deductive systems. In Proc. of the 3rd International Conference on Deductive and Object-Oriented Databases (DOOD), S. Ceri , K. Tanaka , and S. Tsur , Eds. Lecture Notes in Computer Science, vol. 760. Springer, Berlin Heidelberg, 101119.

C. Baral , K. Chancellor , N. Tran , N. Tran , A. M. Joy and M. E. Berens 2004. A knowledge based approach for representing and reasoning about signaling networks. Bioinformatics 20, supplement 1, 1522.

T. Bench-Capon , D. Lowes and A. M McEnery . 1991. Argument-based explanation of logic programs. Knowledge-Based Systems 4, 3, 177183.

A. Bondarenko , P. M. Dung , R. A. Kowalski and F. Toni 1997. An abstract, argumentation-theoretic approach to default reasoning. Artificial Intelligence 93, 1–2, 63101.

P. M. Dung 1995a. An argumentation-theoretic foundation for logic programming. The Journal of Logic Programming 22, 2, 151177.

P. M. Dung 1995b. On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games. Artificial Intelligence 77, 2, 321357.

P. M. Dung , R. A. Kowalski and F. Toni 2006. Dialectic proof procedures for assumption-based, admissible argumentation. Artificial Intelligence 170, 2, 114159.

P. M. Dung , R. A. Kowalski and F. Toni 2009. Assumption-based argumentation. In Argumentation in Artificial Intelligence, G. R. Simari and I. Rahwan , Eds. Springer US, New York, 199218.

P. M. Dung , P. Mancarella and F. Toni 2007. Computing ideal sceptical argumentation. Artificial Intelligence 171, 10–15, 642674.

O. Febbraro , K. Reale and F. Ricca 2011. ASPIDE: Integrated development environment for answer set programming. In Proc. of the 11th International Conference on Logic Programming and Nonmonotonic Reasoning (LPNMR), J. P. Delgrande and W. Faber , Eds. Lecture Notes in Computer Science, vol. 6645. Springer, Berlin Heidelberg, 317330.

A. J. García , C. I. Chesñevar , N. D. Rotstein and G. R. Simari 2013. Formalizing dialectical explanation support for argument-based reasoning in knowledge-based systems. Expert Systems with Applications 40, 8, 32333247.

A. J. García and G. R. Simari 2004. Defeasible logic programming: An argumentative approach. Theory and Practice of Logic Programming 4, 1–2, 95138.

M. Gelfond 2008. Answer sets. In Handbook of Knowledge Representation, F. van Harmelen , V. Lifschitz , and B. Porter , Eds. Foundations of Artificial Intelligence, vol. 3. Elsevier, San Diego, Chapter 7, 285316.

M. Gelfond and V. Lifschitz 1991. Classical negation in logic programs and disjunctive databases. New Generation Computing 9, 3–4, 365385.

G. Governatori , M. J. Maher , G. Antoniou and D. Billington 2004. Argumentation semantics for defeasible logic. Journal of Logic and Computation 14, 5, 675702.

C. Lacave and F. J. Diez 2004. A review of explanation methods for heuristic expert systems. The Knowledge Engineering Review 19, 2, 133146.

B. Moulin , H. Irandoust , M. Bélanger and G. Desbordes 2002. Explanation and argumentation capabilities: Towards the creation of more persuasive agents. Artificial Intelligence Review 17, 3, 169222.

H. Prakken 2010. An abstract framework for argumentation with structured arguments. Argument and Computation 1, 2, 93124.

F. Toni and M. Sergot 2011. Argumentation and answer set programming. In Logic Programming, Knowledge Representation, and Nonmonotonic Reasoning, M. Balduccini and T. C. Son , Eds. Lecture Notes in Computer Science, vol. 6565. Springer, Berlin Heidelberg, 164180.

Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

Theory and Practice of Logic Programming
  • ISSN: 1471-0684
  • EISSN: 1475-3081
  • URL: /core/journals/theory-and-practice-of-logic-programming
Please enter your name
Please enter a valid email address
Who would you like to send this to? *
×

Keywords:

Metrics

Full text views

Total number of HTML views: 0
Total number of PDF views: 16 *
Loading metrics...

Abstract views

Total abstract views: 191 *
Loading metrics...

* Views captured on Cambridge Core between September 2016 - 24th June 2017. This data will be updated every 24 hours.